Shiquan Sun, PhD

Statistical Genomics；Bioinformatics；Biostatistics；Single-Cell and Spatial Omics

[Masahiro Kanai @masakanai]

Our single-nucleus immune multiome atlas is now out in @Nature! 🧬

10M PBMCs from 1,108 @FinnGen_FI donors recruited by @FRCBSresearch, profiled at @broadinstitute KCO with chromatin accessibility and gene expression in the same nuclei, to trace how disease variants act 🧵👇

[Jonny @aiwithjonny]

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❯ ALL BOOKS (40+ Subjects)
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Follow @aiwithjonny for more.

[Amelia Brooks @Amelia_With_Ai]

Best YouTube Playlists to learn Programming:

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[Dr. Alex Wissner-Gross @alexwg]

https://t.co/N2AwpI9f8m

[Agingdoc🩺Dr David Barzilai🔔MD PhD MS MBA DipABLM @agingdoc1]

The dual nature of neuroinflammation in networked brain

https://t.co/iF1VGj6cnx @FrontImmunol

[Fabian Theis @fabian_theis]

🚀 New preprint!
The Human Cytokine Dictionary - 9.7M cells, 12 donors, 90 cytokines - our largest human single-cell perturbation atlas yet. Users can map cytokine activity in their own data. Huge thanks to Lukas, Sören, Larsen, Parse Bio & Seelig lab!
🔗 https://t.co/tB0teJoGez

[Altuna Akalin @AltunaAkalin]

Published📘 "Computational genomics with R" is now available from CRC press. Check out if you want to learn #machineLearning #stats #Rstats #genomics #ChIPseq #rnaseq #BSseq. Big thanks to @VedranFranke @BoraUyar & Jona Ronen, each contributed a chapter. https://t.co/TqLTxXcu7a

[Jonathan Pritchard @jkpritch]

Two new chapters from my free online book in human genetics out this weekend!

These complete Part 3 of the book, on human population structure and history:
3.3: Inferring human prehistory from genetic data [this thread]
3.4: Ancient DNA [next thread]
https://t.co/GHMPCTv6BL

[Nature Reviews Genetics @NatureRevGenet]

The complex non-genetic inheritance of complex traits https://t.co/jcgsgNEpb1 #JournalClub by Merly C. Vogt @helmholtz_diabc @HelmholtzMunich

[Boran @Boran41713825]

Thrilled to announce that I’m joining @PurdueStats and @PurdueBiolSci as a tenure-track assistant professor! Excited for the journey ahead and to contribute to such a vibrant academic community.

[Itai Yanai @ItaiYanai]

In today's Cell, we propose a “developmental constraint” model whereby cancer cell state plasticity is restricted by the organism’s developmental map to access progenitor-like states and differentiated-like states of adjacent lineages.🧵⬇️
https://t.co/1HM7fYQJO4 @AyushiPatel3994

[Manolis Kellis @manoliskellis]

Excited to share our #SingleCell dissection of #Schizophrenia, out in @ScienceMagazine today, reporting 470k cells in 27 cell types across 140 individuals from 2 cohorts,
revealing key insights on #ExcitatoryNeurons, #NeuroDevelopment, #Synapses, #1Cmetabolism, #Genetics, #Subtyping, #NetworkConvergence, #TFs, #DEGs, #GWAS, #RareVariants, and #DiseaseMechanism,
with @Brad_Ruzicka @LabRoussos @ShahinMohammadi @_josedavila #PsychENCODE2
Paper: https://t.co/3pFCOE5ind
Collection: https://t.co/W0lv6l8ofz
Science tweet: https://t.co/pp3zQMiZIN
Big thanks to @NIH, @NIMHgov, #PsychENCODE

[Shiquan Sun, PhD @SunShiquan]

Our new method, TDEseq has been published on @GenomeBiology. It primarily builds upon a linear additive mixed model framework to facilitate the detection of four potential temporal gene expression patterns, i.e., growth, recession, peak, or trough. https://t.co/Gjg4lJ7elI

[Shiquan Sun, PhD @SunShiquan]

Our new method, TDEseq has been published on @GenomeBiology. It primarily builds upon a linear additive mixed model framework to facilitate the detection of four potential temporal gene expression patterns, i.e., growth, recession, peak, or trough. https://t.co/Gjg4lJ7elI

[Shiquan Sun, PhD @SunShiquan]

@yingma0107 Congratulations!

[Bo Wang @BoWang87]

🎉Exciting Update of scGPT 🎉: After receiving significant attention from the community since our April release, we're thrilled to announce the first major update for scGPT - a foundation model for single-cell multi-omic data.

This update integrates community feedback and leverages the latest data release from @cellxgene. It boasts larger pretraining data, and more robust models, and expands the range of application tasks.

Pre-print (V2) available: https://t.co/4aB2c4ZgJy
Access our open-source code and models here: https://t.co/13n0bJvgT2
Detailed tutorials: https://t.co/enNqXqXkdY

Highlights of this update include:

🔬 Introducing the first GPT-style foundation model for single-cell multi-omic data, pretrained on over 33M human cell atlas data.

💡 Our generalist approach enables one model to accomplish multiple tasks in single-cell analysis, including multi-omic integrative analysis and perturbation prediction.

🧬 Discovering gene-gene interactions specific to various conditions using learned attention weights and gene embeddings.

🚀 Uncovered a scaling law showcasing continuous model performance enhancement as data volume increases.

🐾 scGPT model zoo (see github) now offers multiple pre-trained foundation models for various solid organs and a comprehensive pan-cancer model. Begin exploring your data with the most fitting foundation model.

We welcome your thoughts on specialist vs generalist approaches in single-cell studies. Many thanks for the following technical analyses of scGPT:
1. Excellent twittorial by @simocristea: https://t.co/ICq3V78oxG
2. Comprehensive review on LLM in cell biology by @s_batzoglou: https://t.co/xtl5WCXijC
3. Insightful blog by @SalvatoreRaieli: https://t.co/7v8PRv9NNc

Kudos to Haotian (@HAOTIANCUI1) & Chloe (@chloexwang1) for their exemplary work on this project. @VectorInst @pmcc_ai @UHNAIHUB @bradwouters @drbarryrubin @UofT_TCAIREM @UofT_LMP @UofTCompSci @uoftmedicine

[Annals of the Rheumatic Diseases @eular_ARD]

🔍 New study identifies critical cell populations in knee osteoarthritis, offering insights for targeted therapies 🎯.
A step closer to precision medicine in OA management?
#Osteoarthritis #Innovation 🔬 🧬📈
📎 https://t.co/XoboucbVpL

[James Zou @james_y_zou]

New in @naturemethods!

We introduce TISSUE, an uncertainty-aware framework for integrating and using #spatial #transcriptomics. Conformal prediction + spatial biology enhances downstream analyses and discovery 💯

Paper: https://t.co/YUq7XZlq6W
Code: https://t.co/Qs6EKx9Y9t
1/3

[Gabriel Peyré @gabrielpeyre]

Inverse of Laplacian matrix can be used to define covariance kernels with positive pairwise correlations between nodes. https://t.co/sI0gmOfNP0

[Steven Salzberg 💙💛 @StevenSalzberg1]

Major, fatal errors found in the data and methods of a 2020 paper in @Nature, including millions of reads mis-identified as bacteria. The "cancer microbiome" in this study was simply not there. @abrahamgihawi @elapertea @YuchenGe1 @JenniferLu717 https://t.co/z5Aja84kiR